Two lattice computing approaches for the unsupervised segmentation of hyperspectral images

J.W. Boardman, Analysis, understanding and visualization of hyperspectral data as convex sets in n-space, in: Imaging Spectrometry, Proceedings of the SPIE, vol. 2480, 1995, pp. 14–22.

Craig, 1994, Minimum volume transformations for remotely sensed data, IEEE Trans. Geos. Rem. Sensing, 32, 542, 10.1109/36.297973

Duda, 1973

Ganter, 1999

Gonzalez, 2007

Graña, 2007, State of the art in lattice computing for artificial intelligence applications, 233

Graña, 2008

M. Graña, A. d’Anjou, Feature extraction by linear spectral unmixing, in: M. Negoita, R.J. Howlett, L.C. Jain (Eds.), Knowledge-Based Intelligent Information and Engineering Systems. Part I, Lecture Notes in Artificial Intelligence, vol. 3213, Springer, Berlin, 2004, pp. 692–697.

Graña, 2005, Morphological memories for feature extraction in hyperspectral images, 497

M. Graña, J. Gallego, Associative morphological memories for endmember induction, in: Proceedings of the IGARSS’2003, vol. 6, 2003, pp. 3757–3759.

Graña, 2007, Lattice independence, autoassociative morphological memories and unsupervised segmentation of hyperspectral images, 1624

M. Graña, P. Sussner, G.X. Ritter, Associative morphological memories for endmember determination in spectral unmixing, in: Proceedings of the FUZZ-IEEE’03, vol. 2, 2003, pp. 1285–1290.

Graña, 2007, Convex coordinates from lattice independent sets for visual pattern recognition, 99

Hopfield, 1982, Neural networks and physical systems with emergent collective computational abilities, Proc. Natl. Acad. Sci., 79, 2554, 10.1073/pnas.79.8.2554

Ifarraguerri, 1999, Multispectral and hyperspectral image analysis with convex cones, IEEE Trans. Geos. Rem. Sensing, 37, 756, 10.1109/36.752192

Kaburlasos, 2006

Keshava, 2002, Spectral unimixing, IEEE Signal Process. Mag., 19, 44, 10.1109/79.974727

Landgrebe, 2003

Manolakis, 2002, Detection algorithms for hyperspectral imaging applications, IEEE Signal Process. Mag., 19, 29, 10.1109/79.974724

Plaza, 2002, Spatial spatial/spectral endmember extraction by multidimensional morphological operations, IEEE Trans. Geos. Rem. Sensing, 40, 2025, 10.1109/TGRS.2002.802494

Raducanu, 2003, Morphological scale spaces and associative morphological memories: results on robustness and practical applications, J. Math. Imaging Vision, 19, 113, 10.1023/A:1024725414204

Ritter, 1999, Morphological bidirectional associative memories, Neural Networks, 12, 851, 10.1016/S0893-6080(99)00033-7

Ritter, 2006, Fixed points of lattice transforms and lattice associative memories, vol. 144, 165

Ritter, 2007, Efficient autonomous endmember determination using lattice autoassociative memories, 1632

Ritter, 1998, Morphological associative memories, IEEE Trans. Neural Networks, 9, 281, 10.1109/72.661123

Ritter, 2003, Lattice algebra approach to single-neuron computation, IEEE Trans. Neural Networks, 14, 282, 10.1109/TNN.2003.809427

Ritter, 2003, Reconstruction of patterns from noisy inputs using morphological associative memories, J. Math. Imaging Vision, 19, 95, 10.1023/A:1024773330134

G.X. Ritter, G. Urcid, M.S. Schmalz, Autonomous single-pass endmember approximation using lattice auto-associative memories, Neurocomputing (2009), this issue, doi:10.1016/j.neucom.2008.06.025.

Ritter, 2000

Sussner, 2001, Observations on morphological associative memories and the kernel method

Sussner, 2003, Generalizing operations of binary autoassociative morphological memories using fuzzy set theory, J. Math. Imaging Vision, 19, 81, 10.1023/A:1024721313295

Villaverde, 2007, Morphological neural networks and vision based simultaneous localization and mapping, Integrated Computer-Aided Eng., 14, 355, 10.3233/ICA-2007-14406

M.E. Winter, An algorithm for fast autonomous spectral endmember determination in hyperspectral analysis, in: Imaging Spectrometry, Proceedings of the SPIE, vol. 3753, 1999, pp. 266–275.

Xu, 2003, 10.1007/978-3-540-44847-1